The rationale for estimating the propensity scores is the following. Randomization guarantees that there is no confounding on expectation [1]}. Nevertheless, covariate balance is a large-sample property, and one may still observe residual covariate imbalances between treatment groups due to chance, especially when the trial sample size is small [2]}. As formulated by Senn [1]}, “over all randomizations the groups are balanced; for a particular randomization they are unbalanced.” The use of estimated propensity scores allows to correct for random finite-sample imbalances in prognostic baseline covariates. In the RCT literature, inverse probability of treatment weighting is an established approach for covariate adjustment [4]}, and has increased precision, efficiency and power with respect to unadjusted analyses in the estimation of marginal treatment effects [5]}, [6]}.
